Autonomous Robots

, Volume 42, Issue 5, pp 1011–1021 | Cite as

Robot adaptation to human physical fatigue in human–robot co-manipulation

  • Luka PeternelEmail author
  • Nikos Tsagarakis
  • Darwin Caldwell
  • Arash Ajoudani
Part of the following topical collections:
  1. Special Issue: Learning for Human-Robot Collaboration


In this paper, we propose a novel method for human–robot collaboration, where the robot physical behaviour is adapted online to the human motor fatigue. The robot starts as a follower and imitates the human. As the collaborative task is performed under the human lead, the robot gradually learns the parameters and trajectories related to the task execution. In the meantime, the robot monitors the human fatigue during the task production. When a predefined level of fatigue is indicated, the robot uses the learnt skill to take over physically demanding aspects of the task and lets the human recover some of the strength. The human remains present to perform aspects of collaborative task that the robot cannot fully take over and maintains the overall supervision. The robot adaptation system is based on the Dynamical Movement Primitives, Locally Weighted Regression and Adaptive Frequency Oscillators. The estimation of the human motor fatigue is carried out using a proposed online model, which is based on the human muscle activity measured by the electromyography. We demonstrate the proposed approach with experiments on real-world co-manipulation tasks: material sawing and surface polishing.


Physical human–robot collaboration Human fatigue Robot learning Human–robot interface 

Supplementary material

Supplementary material 1 (mp4 21007 KB)


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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  1. 1.HRI² Lab and HHCM Lab, Department of Advanced RoboticsIstituto Italiano di TecnologiaGenoaItaly

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